Rong kunci sing beda bisa hash menyang bucket sing padha — tabrakan. Tabel hash tetep O(1) rata-rata dening ngatasi tabrakan lan ngubah ukuran sadurunge bucket dadi penak, dikontrol dening faktor beban.
Separate chaining: each bucket holds a list
[3] -> ("cat",9) -> ("rat",2) # both hashed to 3
Open addressing: probe to the next free slot
hash=3 taken -> try 4 -> try 5 ... (linear probing)
load factor α = number_of_entries / number_of_buckets
α rises -> more collisions -> slower lookups
When α exceeds a threshold (e.g. 0.75):
-> allocate a bigger array (usually 2x)
-> REHASH every existing key into new buckets
# Conceptual resize
def _resize(self):
old = self.buckets
self.buckets = [None] * (len(old) * 2)
for entry in all_entries(old):
self._insert(entry.key, entry.value) # rehash into new array
| Operasi | Rata-rata | Paling parah |
|---|---|---|
| lookup / insert / delete | O(1) | O(n) |
| resize tunggal | — | O(n) |
| insert (amortized, karo resizing) | O(1) | — |
Resize iku O(n) nanging kejadiyan jarang, dadi amortizes menyang O(1) per insert.
Internals iki nerangake kenapa peta hash cepet rata-rata nanging bisa lonjor menyang O(n) — bisnis kanggo kode-sensitif-performance lan pertahanan input-adversarial (hash-flooding). Megerteni faktor beban uga nerangake memory/speed tuning knobs sing kadhapuk dening perpustakaan nyata.